Chin-Ling Chen | Cryptography | Outstanding Scientist Award

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Prof Dr. Chin-Ling Chen | Cryptography | Outstanding Scientist Award

Professor at Chaoyang University of Technology, Taiwan

Summary:

Prof. Dr. Chin-Ling Chen is a prominent researcher and academic known for his expertise in blockchain technology, cryptography, authentication, and network security. He has authored over 170 articles in prestigious SCI/SSCI international journals and holds 12 patents in Taiwan. From 2006 to 2015, he was recognized as a distinguished researcher at Chaoyang University of Technology, where he currently serves as a faculty member. Prof. Chen has actively contributed to the academic community by reviewing over 450 journal articles and serving on the editorial boards of several journals, including PLOS ONE and the International Journal on Artificial Intelligence Tools. His significant research contributions have advanced the fields of computer security, privacy, and digital signatures, positioning him as a leading figure in his areas of study.

Profile:

Education:

Prof. Dr. Chin-Ling Chen holds a distinguished educational background that has laid the foundation for his extensive research career. He earned his Bachelor’s degree in Computer Science and Information Engineering from National Changhua University of Education in Taiwan. He then pursued his Master’s degree in Computer Science from National Tsing Hua University, further enhancing his expertise in the field. Prof. Chen completed his Ph.D. in Computer Science and Engineering at National Chung Cheng University, where he focused on cutting-edge topics such as cryptography and network security. His strong academic training has significantly contributed to his prolific output and innovative research contributions in various domains, including blockchain technology, authentication, and wireless sensor networks.

Professional Experience:

Prof. Dr. Chin-Ling Chen has an extensive professional background in academia and research, primarily at Chaoyang University of Technology, where he has served as a faculty member and researcher. His career spans several years, during which he has made significant contributions to the fields of blockchain, cryptography, authentication, and network security. Prof. Chen has been recognized as a distinguished researcher annually from 2006 to 2015, highlighting his commitment to excellence in research and education. In addition to his teaching responsibilities, he has actively participated in peer review processes, evaluating over 450 articles for various SCI/SSCI journals. His editorial roles include memberships on the editorial boards of respected journals such as PLOS ONE and the International Journal on Artificial Intelligence Tools, reflecting his influence and leadership within the academic community.

Research Interests:

Prof. Dr. Chin-Ling Chen’s research interests encompass a broad range of topics in computer science and security, focusing on areas such as blockchain technology, cryptography, authentication, and network security. His work addresses critical issues in computer security and privacy, exploring innovative solutions for web services, mobile commerce (M-Commerce), and e-commerce applications. Prof. Chen also investigates digital signatures, radio frequency identification (RFID) systems, wireless sensor networks, and vehicular ad hoc networks. With over 170 publications in esteemed SCI/SSCI international journals, his contributions to these fields are significant, complemented by 12 patents in Taiwan. His research not only advances theoretical knowledge but also has practical implications, enhancing the security and privacy of modern technological systems.

Skills:

Prof. Dr. Chin-Ling Chen possesses a diverse skill set that is highly relevant to his research in computer science and security. He is proficient in blockchain technology and cryptographic techniques, enabling him to develop secure systems and applications. His expertise in authentication methods and network security allows him to address complex challenges related to data protection and privacy. Prof. Chen is also skilled in designing and implementing secure web services and e-commerce platforms, ensuring safe transactions and user confidentiality. Additionally, he has significant experience in radio frequency identification (RFID) technology and wireless sensor networks, contributing to advancements in IoT and vehicular ad hoc networks. His extensive background in research methodology and peer review further enhances his ability to contribute to the academic community and drive innovation in the field.

Conclution:

Prof. Dr. Chin-Ling Chen’s significant contributions to research, along with his extensive publication record and innovative patents, position him as a leading scientist in his field. His ongoing dedication to advancing technology and security makes him a highly deserving candidate for the Research for Outstanding Scientist Award.

Publication Top Noted:

Conformation of EPC Class 1 Generation 2 standards RFID system with mutual authentication and privacy protection

  • Cited By: 159
  • Year: 2009
  • Journal: Engineering Applications of Artificial Intelligence, 22(8), 1284-1291

An efficient user authentication and user anonymity scheme with provable security for IoT-based medical care system

  • Cited By: 137
  • Year: 2017
  • Journal: Sensors, 17(7), 1482

An extended chaotic maps-based key agreement protocol with user anonymity

  • Cited By: 114
  • Year: 2012
  • Journal: Nonlinear Dynamics, 69, 79-87

Mobile device integration of a fingerprint biometric remote authentication scheme

  • Cited By: 93
  • Year: 2012
  • Journal: International Journal of Communication Systems, 25(5), 585-597

An intelligent and secure health monitoring scheme using IoT sensor based on cloud computing

  • Cited By: 81
  • Year: 2017
  • Journal: Journal of Sensors, 2017(1), 3734764

A privacy authentication scheme based on cloud for medical environment

  • Cited By: 77
  • Year: 2014
  • Journal: Journal of Medical Systems, 38, 1-16

The design of a secure anonymous internet voting system

  • Cited By: 76
  • Year: 2004
  • Journal: Computers & Security, 23(4), 330-337

A traceable and privacy-preserving authentication for UAV communication control system

  • Cited By: 71
  • Year: 2020
  • Journal: Electronics, 9(1), 62

A secure medical data exchange protocol based on cloud environment

  • Cited By: 68
  • Year: 2014
  • Journal: Journal of Medical Systems, 38, 1-12

Collaborative learning by teaching: A pedagogy between learner-centered and learner-driven

  • Cited By: 59
  • Year: 2019
  • Journal: Sustainability, 11(4), 1174

Lidan Wang | Chaotic Cryptography | Best Researcher Award

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Prof. Lidan Wang | Chaotic Cryptography | Best Researcher Award

Supervisor at Southwest University, China

Summary:

Prof. Lidan Wang is a distinguished professor and doctoral supervisor in the College of Artificial Intelligence at Southwest University in Chongqing, China. She earned her B.E. degree in Automatic Control from Nanjing University of Science and Technology in 1999 and her Ph.D. in Computer Software and Theory from Chongqing University in 2008. Furthering her academic journey, she completed post-doctoral research at Chongqing University in 2012. Prof. Wang’s research focuses on artificial intelligence, particularly in the areas of artificial neural networks, neural morphological systems, memristor devices and systems, chaotic systems, and nonlinear circuit design. She has led over 20 significant research projects, including those funded by the National Key R&D Program and the National Natural Science Foundation of China.

 

Profile:

Education:

Prof. Lidan Wang earned her Bachelor of Science degree in Electrical Engineering from Nanjing University of Science and Technology, China, in 1996. She pursued her Master’s degree and Ph.D. in Electrical Engineering at Chongqing University, China, completing her Ph.D. in 2008. Additionally, Prof. Wang conducted post-doctoral research at Chongqing University from 2012 to 2014, further advancing her expertise in the field of artificial intelligence and neural networks.

Professional Experience:

Prof. Lidan Wang began her academic career as an Associate Professor at Southwest University, Chongqing, China, serving from 2008 to 2012. She was promoted to Professor in 2013, a position she continues to hold. In addition to her role at Southwest University, Prof. Wang has gained international experience through various visiting professorships, including at Imperial College London, Nanyang Technological University, Texas A&M University at Qatar, and the University of Tasmania. Her leadership extends beyond teaching and research, as she currently serves as the deputy director of the Chongqing Key Laboratory of Brain-like Computing and Intelligent Control, Secretary General of the Chongqing Artificial Intelligence Society, and Director of the Chongqing Young Science and Technology Leaders Association.

Research Interests:

Prof. Lidan Wang’s research interests lie primarily in the realm of artificial intelligence, with a strong focus on artificial neural networks and neural morphological systems. Her work explores memristor devices and systems, chaotic systems, and nonlinear circuit design. Prof. Wang is particularly engaged in advancing the understanding and application of these technologies, aiming to develop innovative solutions and systems that integrate these complex components. Her research contributes significantly to the fields of artificial intelligence and neural network technologies.

Skills:

Prof. Lidan Wang possesses advanced skills in artificial intelligence, encompassing artificial neural networks and neural morphological systems. She is proficient in the design and implementation of memristor devices and systems, as well as in the analysis and development of chaotic systems and nonlinear circuits. Her expertise extends to leading and managing research projects, having successfully undertaken numerous high-profile projects including National Key R&D Program subprojects and various funding initiatives. Additionally, Prof. Wang has a strong background in patent development and academic publishing, contributing to her distinguished reputation in the scientific community.

Conclution:

Given her exceptional research contributions, extensive publication record, numerous awards, and significant leadership roles, Prof. Lidan Wang is a highly deserving candidate for the Best Researcher Award. Her work not only advances the field of artificial intelligence but also inspires and influences the global research community.

Publication Tob Noted:

Memristor-based cellular nonlinear/neural network: design, analysis, and applications

  • Authors: S. Duan, X. Hu, Z. Dong, L. Wang, P. Mazumder
  • Journal: IEEE Transactions on Neural Networks and Learning Systems
  • Volume: 26, Issue 6
  • Pages: 1202-1213
  • Year: 2014
  • Citations: 297

Electronic nose feature extraction methods: A review

  • Authors: J. Yan, X. Guo, S. Duan, P. Jia, L. Wang, C. Peng, S. Zhang
  • Journal: Sensors
  • Volume: 15, Issue 11
  • Pages: 27804-27831
  • Year: 2015
  • Citations: 296

Exponential stability of complex-valued memristive recurrent neural networks

  • Authors: H. Wang, S. Duan, T. Huang, L. Wang, C. Li
  • Journal: IEEE Transactions on Neural Networks and Learning Systems
  • Volume: 28, Issue 3
  • Pages: 766-771
  • Year: 2016
  • Citations: 159

A novel memristive Hopfield neural network with application in associative memory

  • Authors: J. Yang, L. Wang, Y. Wang, T. Guo
  • Journal: Neurocomputing
  • Volume: 227
  • Pages: 142-148
  • Year: 2017
  • Citations: 158

Memristor model and its application for chaos generation

  • Authors: L. Wang, E. Drakakis, S. Duan, P. He, X. Liao
  • Journal: International Journal of Bifurcation and Chaos
  • Volume: 22, Issue 08
  • Article Number: 1250205
  • Year: 2012
  • Citations: 147

Volatile and nonvolatile memristive devices for neuromorphic computing

  • Authors: G. Zhou, Z. Wang, B. Sun, F. Zhou, L. Sun, H. Zhao, X. Hu, X. Peng, J. Yan, …
  • Journal: Advanced Electronic Materials
  • Volume: 8, Issue 7
  • Article Number: 2101127
  • Year: 2022
  • Citations: 129

Resistive switching memory integrated with amorphous carbon-based nanogenerators for self-powered device

  • Authors: G. Zhou, Z. Ren, L. Wang, J. Wu, B. Sun, A. Zhou, G. Zhang, S. Zheng, S. Duan, …
  • Journal: Nano Energy
  • Volume: 63
  • Article Number: 103793
  • Year: 2019
  • Citations: 126

Artificial and wearable albumen protein memristor arrays with integrated memory logic gate functionality

  • Authors: G. Zhou, Z. Ren, L. Wang, B. Sun, S. Duan, Q. Song
  • Journal: Materials Horizons
  • Volume: 6, Issue 9
  • Pages: 1877-1882
  • Year: 2019
  • Citations: 123

Capacitive effect: An original of the resistive switching memory

  • Authors: G. Zhou, Z. Ren, B. Sun, J. Wu, Z. Zou, S. Zheng, L. Wang, S. Duan, Q. Song
  • Journal: Nano Energy
  • Volume: 68
  • Article Number: 104386
  • Year: 2020
  • Citations: 118